Which prerequisites must be satisfied before automation?

RUBE_SEARCH_TOOLS must be available and an active Datagma connection must exist via RUBE_MANAGE_CONNECTIONS with the datagma toolkit.

Should I hardcode tool slugs?

No. Always call RUBE_SEARCH_TOOLS to fetch current tool slugs and schemas; hardcoding can break workflows when schemas change.

What must be included when executing tools?

Include a memory payload in RUBE_MULTI_EXECUTE_TOOL, and provide a valid session_id; ensure the tool_slug matches the discovered results and the input conforms to the schema.

datagma-automation

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Datagma Automation via Rube MCP

Automate Datagma operations through Composio's Datagma toolkit via Rube MCP.

Toolkit docs: composio.dev/toolkits/datagma

Prerequisites

Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
Active Datagma connection via RUBE_MANAGE_CONNECTIONS with toolkit datagma
Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
Call RUBE_MANAGE_CONNECTIONS with toolkit datagma
If connection is not ACTIVE, follow the returned auth link to complete setup
Confirm connection status shows ACTIVE before running any workflows

Tool Discovery

Always discover available tools before executing workflows:

RUBE_SEARCH_TOOLS
queries: [{use_case: "Datagma operations", known_fields: ""}]
session: {generate_id: true}

This returns available tool slugs, input schemas, recommended execution plans, and known pitfalls.

Core Workflow Pattern

Step 1: Discover Available Tools

RUBE_SEARCH_TOOLS
queries: [{use_case: "your specific Datagma task"}]
session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS
toolkits: ["datagma"]
session_id: "your_session_id"

Step 3: Execute Tools

RUBE_MULTI_EXECUTE_TOOL
tools: [{
  tool_slug: "TOOL_SLUG_FROM_SEARCH",
  arguments: {/* schema-compliant args from search results */}
}]
memory: {}
session_id: "your_session_id"

Known Pitfalls

Always search first: Tool schemas change. Never hardcode tool slugs or arguments without calling RUBE_SEARCH_TOOLS
Check connection: Verify RUBE_MANAGE_CONNECTIONS shows ACTIVE status before executing tools
Schema compliance: Use exact field names and types from the search results
Memory parameter: Always include memory in RUBE_MULTI_EXECUTE_TOOL calls, even if empty ({})
Session reuse: Reuse session IDs within a workflow. Generate new ones for new workflows
Pagination: Check responses for pagination tokens and continue fetching until complete

Quick Reference

Operation	Approach
Find tools	`RUBE_SEARCH_TOOLS` with Datagma-specific use case
Connect	`RUBE_MANAGE_CONNECTIONS` with toolkit `datagma`
Execute	`RUBE_MULTI_EXECUTE_TOOL` with discovered tool slugs
Bulk ops	`RUBE_REMOTE_WORKBENCH` with `run_composio_tool()`
Full schema	`RUBE_GET_TOOL_SCHEMAS` for tools with `schemaRef`

Powered by Composio

Source

git clone https://github.com/ComposioHQ/awesome-claude-skills/blob/master/composio-skills/datagma-automation/SKILL.mdView on GitHub

Overview

Automate Datagma operations through Composio's Datagma toolkit using Rube MCP. Always search for current tool schemas first with RUBE_SEARCH_TOOLS to avoid broken workflows. This approach keeps your automation aligned with up-to-date tool definitions.

How This Skill Works

Connect to Rube MCP and ensure an active Datagma connection via RUBE_MANAGE_CONNECTIONS with the datagma toolkit. Discover available tools and their schemas using RUBE_SEARCH_TOOLS before execution. Execute the selected tool with RUBE_MULTI_EXECUTE_TOOL, including memory payloads and the proper session_id, then reuse or refresh sessions as needed.

When to Use It

You need to automate a Datagma task and want up-to-date tool schemas before running.
You must verify that RUBE_SEARCH_TOOLS is available and the Datagma connection is ACTIVE.
Integrating Datagma tasks into a Composio workflow where tool slugs may change over time.
You need to execute a discovered tool with precise arguments and a memory payload.
You want to reuse session IDs across steps or generate new sessions for new workflows.

Quick Start

Step 1: Ensure Rube MCP is configured and RUBE_SEARCH_TOOLS is accessible.
Step 2: Run RUBE_SEARCH_TOOLS to discover Datagma tools and their input schemas.
Step 3: Establish/verify connection with RUBE_MANAGE_CONNECTIONS and execute a tool with RUBE_MULTI_EXECUTE_TOOL using memory and session_id.

Best Practices

Always call RUBE_SEARCH_TOOLS before running workflows to fetch current tool slugs and schemas.
Check that RUBE_MANAGE_CONNECTIONS reports ACTIVE before executing tools.
Use exact field names and types from the search results; avoid hardcoding slugs or arguments.
Include the memory parameter in RUBE_MULTI_EXECUTE_TOOL calls, even if empty ({}).
Reuse session IDs within a workflow; generate new sessions only for new tasks.

Example Use Cases

Discover latest Datagma tool slugs, select a task, and execute with correct arguments in a nightly automation.
Validate an active Datagma connection, fetch tool schemas, and run a dataset operation across multiple records.
Batch-run multiple Datagma operations by discovering tools once, then iterating execute calls with updated inputs.
Recover from a disconnected state by re-establishing the connection, discovering tools, and resuming with the same session ID.
Handle pagination tokens from tool discovery responses and continue fetching all relevant schemas before execution.

Frequently Asked Questions

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